Basics of AI/ML
Pradipta Biswas · 2026
From human intelligence, this chapter will introduce basic concepts of artificial intelligence (AI). While AI is a common buzzword everywhere now, the topic of AI was not always popular – it suffered many ups and downs in terms of application, prospective danger and subsequent academic or industrial interest. This chapter will start with a brief history of the concept of automation, robots and artificial intelligence. While AI can be described or explained in different ways, we will classify different AI models in terms of underlying knowledge representation. As our final goal will be to develop an intelligent user interface or interaction, different types of knowledge representation will help us decide appropriate encoding techniques for incorporating AI in user interface and user experience (UI/UX) design. Among different types of machine learning (ML) models, we will briefly introduce linear regression and neural networks as examples of supervised ML models, the basic context of cluster analysis or unsupervised machine learning and using reinforcement learning for motion planning of autonomous agents. The chapter aims to provide a basic understanding of concepts instead of detailed mathematical foundations, which may be found in the cited lecture notes.